We use a semi supervised learning technique for building our ASR model [1]} [2]}. Language Models also play a key role in the E2E ASR systems because of their potential to predict and correct the upcoming words based on the text corpus. The Language Model (LM) used in this paper is a statistical LM built from KenLM[3]} toolkit.
